Title | ||
---|---|---|
Scan-Chain-Fault Diagnosis Using Regressions in Cryptographic Chips for Wireless Sensor Networks. |
Abstract | ||
---|---|---|
Scan structures, which are widely used in cryptographic circuits for wireless sensor networks applications, are essential for testing very-large-scale integration (VLSI) circuits. Faults in cryptographic circuits can be effectively screened out by improving testability and test coverage using a scan structure. Additionally, scan testing contributes to yield improvement by identifying fault locations. However, faults in circuits cannot be tested when a fault occurs in the scan structure. Moreover, various defects occurring early in the manufacturing process are expressed as faults of scan chains. Therefore, scan-chain diagnosis is crucial. However, it is difficult to obtain a sufficiently high diagnosis resolution and accuracy through the conventional scan-chain diagnosis. Therefore, this article proposes a novel scan-chain diagnosis method using regression and fan-in and fan-out filters that require shorter training and diagnosis times than existing scan-chain diagnoses do. The fan-in and fan-out filters, generated using a circuit logic structure, can highlight important features and remove unnecessary features from raw failure vectors, thereby converting the raw failure vectors to fan-in and fan-out vectors without compromising the diagnosis accuracy. Experimental results confirm that the proposed scan-chain-diagnosis method can efficiently provide higher resolutions and accuracies with shorter training and diagnosis times. |
Year | DOI | Venue |
---|---|---|
2020 | 10.3390/s20174771 | SENSORS |
Keywords | DocType | Volume |
cryptography,wireless sensor networks,machine learning,scan-chain diagnosis | Journal | 20 |
Issue | ISSN | Citations |
17 | 1424-8220 | 1 |
PageRank | References | Authors |
0.36 | 12 | 3 |
Name | Order | Citations | PageRank |
---|---|---|---|
Hyunyul Lim | 1 | 20 | 4.46 |
Minho Cheong | 2 | 1 | 0.36 |
Sungho Kang | 3 | 436 | 78.44 |